Pandas Profiling Report

Dataset statistics

Number of variables	9
Number of observations	768
Missing cells	652
Missing cells (%)	9.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	54.1 KiB
Average record size in memory	72.2 B

Variable types

Numeric	8
Categorical	1

Warnings

`BloodPressure` has 35 (4.6%) missing values	Missing
`SkinThickness` has 227 (29.6%) missing values	Missing
`Insulin` has 374 (48.7%) missing values	Missing
`BMI` has 11 (1.4%) missing values	Missing
`Pregnancies` has 111 (14.5%) zeros	Zeros

Reproduction

Analysis started	2021-02-17 02:23:36.692228
Analysis finished	2021-02-17 02:23:56.247574
Duration	19.56 seconds
Software version	pandas-profiling v2.10.1
Download configuration	config.yaml

Pregnancies
Real number (ℝ_≥0)

ZEROS

Distinct	17
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.845052083
Minimum	0
Maximum	17
Zeros	111
Zeros (%)	14.5%
Memory size	6.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	3
Q3	6
95-th percentile	10
Maximum	17
Range	17
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.369578063
Coefficient of variation (CV)	0.8763413316
Kurtosis	0.1592197775
Mean	3.845052083
Median Absolute Deviation (MAD)	2
Skewness	0.9016739792
Sum	2953
Variance	11.35405632
Monotocity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	135	17.6%
0	111	14.5%
2	103	13.4%
3	75	9.8%
4	68	8.9%
5	57	7.4%
6	50	6.5%
7	45	5.9%
8	38	4.9%
9	28	3.6%
Other values (7)	58	7.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	111	14.5%
1	135	17.6%
2	103	13.4%
3	75	9.8%
4	68	8.9%

Value	Count	Frequency (%)
17	1	0.1%
15	1	0.1%
14	2	0.3%
13	10	1.3%
12	9	1.2%

Glucose
Real number (ℝ_≥0)

Distinct	135
Distinct (%)	17.7%
Missing	5
Missing (%)	0.7%
Infinite	0
Infinite (%)	0.0%

Mean	121.6867628
Minimum	44
Maximum	199
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	44
5-th percentile	80
Q1	99
median	117
Q3	141
95-th percentile	181
Maximum	199
Range	155
Interquartile range (IQR)	42

Descriptive statistics

Standard deviation	30.53564107
Coefficient of variation (CV)	0.2509364238
Kurtosis	-0.2770397069
Mean	121.6867628
Median Absolute Deviation (MAD)	20
Skewness	0.5309885349
Sum	92847
Variance	932.4253757
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	17	2.2%
99	17	2.2%
111	14	1.8%
106	14	1.8%
129	14	1.8%
125	14	1.8%
105	13	1.7%
95	13	1.7%
112	13	1.7%
102	13	1.7%
Other values (125)	621	80.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
44	1	0.1%
56	1	0.1%
57	2	0.3%
61	1	0.1%
62	1	0.1%

Value	Count	Frequency (%)
199	1	0.1%
198	1	0.1%
197	4	0.5%
196	3	0.4%
195	2	0.3%

BloodPressure
Real number (ℝ_≥0)

MISSING

Distinct	46
Distinct (%)	6.3%
Missing	35
Missing (%)	4.6%
Infinite	0
Infinite (%)	0.0%

Mean	72.40518417
Minimum	24
Maximum	122
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	24
5-th percentile	52
Q1	64
median	72
Q3	80
95-th percentile	92
Maximum	122
Range	98
Interquartile range (IQR)	16

Descriptive statistics

Standard deviation	12.38215821
Coefficient of variation (CV)	0.1710120394
Kurtosis	0.9111578979
Mean	72.40518417
Median Absolute Deviation (MAD)	8
Skewness	0.1341527317
Sum	53073
Variance	153.3178419
Monotocity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
70	57	7.4%
74	52	6.8%
78	45	5.9%
68	45	5.9%
72	44	5.7%
64	43	5.6%
80	40	5.2%
76	39	5.1%
60	37	4.8%
62	34	4.4%
Other values (36)	297	38.7%
(Missing)	35	4.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
24	1	0.1%
30	2	0.3%
38	1	0.1%
40	1	0.1%
44	4	0.5%

Value	Count	Frequency (%)
122	1	0.1%
114	1	0.1%
110	3	0.4%
108	2	0.3%
106	3	0.4%

SkinThickness
Real number (ℝ_≥0)

MISSING

Distinct	50
Distinct (%)	9.2%
Missing	227
Missing (%)	29.6%
Infinite	0
Infinite (%)	0.0%

Mean	29.15341959
Minimum	7
Maximum	99
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	7
5-th percentile	13
Q1	22
median	29
Q3	36
95-th percentile	46
Maximum	99
Range	92
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	10.47698237
Coefficient of variation (CV)	0.3593740465
Kurtosis	2.935491262
Mean	29.15341959
Median Absolute Deviation (MAD)	7
Skewness	0.690619014
Sum	15772
Variance	109.7671596
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	31	4.0%
30	27	3.5%
27	23	3.0%
23	22	2.9%
33	20	2.6%
28	20	2.6%
18	20	2.6%
31	19	2.5%
19	18	2.3%
39	18	2.3%
Other values (40)	323	42.1%
(Missing)	227	29.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
7	2	0.3%
8	2	0.3%
10	5	0.7%
11	6	0.8%
12	7	0.9%

Value	Count	Frequency (%)
99	1	0.1%
63	1	0.1%
60	1	0.1%
56	1	0.1%
54	2	0.3%

Insulin
Real number (ℝ_≥0)

MISSING

Distinct	185
Distinct (%)	47.0%
Missing	374
Missing (%)	48.7%
Infinite	0
Infinite (%)	0.0%

Mean	155.5482234
Minimum	14
Maximum	846
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	14
5-th percentile	41.65
Q1	76.25
median	125
Q3	190
95-th percentile	395.5
Maximum	846
Range	832
Interquartile range (IQR)	113.75

Descriptive statistics

Standard deviation	118.7758552
Coefficient of variation (CV)	0.7635950616
Kurtosis	6.370521815
Mean	155.5482234
Median Absolute Deviation (MAD)	55
Skewness	2.166463844
Sum	61286
Variance	14107.70378
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
105	11	1.4%
140	9	1.2%
130	9	1.2%
120	8	1.0%
94	7	0.9%
100	7	0.9%
180	7	0.9%
110	6	0.8%
135	6	0.8%
115	6	0.8%
Other values (175)	318	41.4%
(Missing)	374	48.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
14	1	0.1%
15	1	0.1%
16	1	0.1%
18	2	0.3%
22	1	0.1%

Value	Count	Frequency (%)
846	1	0.1%
744	1	0.1%
680	1	0.1%
600	1	0.1%
579	1	0.1%

BMI
Real number (ℝ_≥0)

MISSING

Distinct	247
Distinct (%)	32.6%
Missing	11
Missing (%)	1.4%
Infinite	0
Infinite (%)	0.0%

Mean	32.45746367
Minimum	18.2
Maximum	67.1
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	18.2
5-th percentile	22.2
Q1	27.5
median	32.3
Q3	36.6
95-th percentile	44.5
Maximum	67.1
Range	48.9
Interquartile range (IQR)	9.1

Descriptive statistics

Standard deviation	6.924988332
Coefficient of variation (CV)	0.2133558063
Kurtosis	0.8633790278
Mean	32.45746367
Median Absolute Deviation (MAD)	4.6
Skewness	0.5939697506
Sum	24570.3
Variance	47.9554634
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	13	1.7%
31.6	12	1.6%
31.2	12	1.6%
33.3	10	1.3%
32.4	10	1.3%
32.8	9	1.2%
30.8	9	1.2%
32.9	9	1.2%
30.1	9	1.2%
29.7	8	1.0%
Other values (237)	656	85.4%
(Missing)	11	1.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18.2	3	0.4%
18.4	1	0.1%
19.1	1	0.1%
19.3	1	0.1%
19.4	1	0.1%

Value	Count	Frequency (%)
67.1	1	0.1%
59.4	1	0.1%
57.3	1	0.1%
55	1	0.1%
53.2	1	0.1%

DiabetesPedigreeFunction
Real number (ℝ_≥0)

Distinct	517
Distinct (%)	67.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.4718763021
Minimum	0.078
Maximum	2.42
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	0.078
5-th percentile	0.14035
Q1	0.24375
median	0.3725
Q3	0.62625
95-th percentile	1.13285
Maximum	2.42
Range	2.342
Interquartile range (IQR)	0.3825

Descriptive statistics

Standard deviation	0.331328595
Coefficient of variation (CV)	0.7021513764
Kurtosis	5.594953528
Mean	0.4718763021
Median Absolute Deviation (MAD)	0.1675
Skewness	1.919911066
Sum	362.401
Variance	0.1097786379
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.254	6	0.8%
0.258	6	0.8%
0.259	5	0.7%
0.238	5	0.7%
0.207	5	0.7%
0.268	5	0.7%
0.261	5	0.7%
0.167	4	0.5%
0.19	4	0.5%
0.27	4	0.5%
Other values (507)	719	93.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.078	1	0.1%
0.084	1	0.1%
0.085	2	0.3%
0.088	2	0.3%
0.089	1	0.1%

Value	Count	Frequency (%)
2.42	1	0.1%
2.329	1	0.1%
2.288	1	0.1%
2.137	1	0.1%
1.893	1	0.1%

Age
Real number (ℝ_≥0)

Distinct	52
Distinct (%)	6.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	33.24088542
Minimum	21
Maximum	81
Zeros	0
Zeros (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	21
5-th percentile	21
Q1	24
median	29
Q3	41
95-th percentile	58
Maximum	81
Range	60
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	11.76023154
Coefficient of variation (CV)	0.3537881556
Kurtosis	0.6431588885
Mean	33.24088542
Median Absolute Deviation (MAD)	7
Skewness	1.129596701
Sum	25529
Variance	138.3030459
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	72	9.4%
21	63	8.2%
25	48	6.2%
24	46	6.0%
23	38	4.9%
28	35	4.6%
26	33	4.3%
27	32	4.2%
29	29	3.8%
31	24	3.1%
Other values (42)	348	45.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	63	8.2%
22	72	9.4%
23	38	4.9%
24	46	6.0%
25	48	6.2%

Value	Count	Frequency (%)
81	1	0.1%
72	1	0.1%
70	1	0.1%
69	2	0.3%
68	1	0.1%

Outcome
Categorical

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	6.1 KiB

0	500
1	268

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	768
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	1

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Most occurring characters

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	768	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	768	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	768	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
0	6	148.0	72.0	35.0	NaN	33.6	0.627	50	1
1	1	85.0	66.0	29.0	NaN	26.6	0.351	31	0
2	8	183.0	64.0	NaN	NaN	23.3	0.672	32	1
3	1	89.0	66.0	23.0	94.0	28.1	0.167	21	0
4	0	137.0	40.0	35.0	168.0	43.1	2.288	33	1
5	5	116.0	74.0	NaN	NaN	25.6	0.201	30	0
6	3	78.0	50.0	32.0	88.0	31.0	0.248	26	1
7	10	115.0	NaN	NaN	NaN	35.3	0.134	29	0
8	2	197.0	70.0	45.0	543.0	30.5	0.158	53	1
9	8	125.0	96.0	NaN	NaN	NaN	0.232	54	1

Last rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
758	1	106.0	76.0	NaN	NaN	37.5	0.197	26	0
759	6	190.0	92.0	NaN	NaN	35.5	0.278	66	1
760	2	88.0	58.0	26.0	16.0	28.4	0.766	22	0
761	9	170.0	74.0	31.0	NaN	44.0	0.403	43	1
762	9	89.0	62.0	NaN	NaN	22.5	0.142	33	0
763	10	101.0	76.0	48.0	180.0	32.9	0.171	63	0
764	2	122.0	70.0	27.0	NaN	36.8	0.340	27	0
765	5	121.0	72.0	23.0	112.0	26.2	0.245	30	0
766	1	126.0	60.0	NaN	NaN	30.1	0.349	47	1
767	1	93.0	70.0	31.0	NaN	30.4	0.315	23	0

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows